Data Operations Analyst .

My client, one of the big names in the iGaming industry, is looking for a Data Operations Analyst will help ensure the reliability and accuracy of client-facing data platforms. This position focuses on daily monitoring of data pipelines, validation of cross-system consistency, and initial troubleshooting. 

Main Responsibilities:

• Monitor data pipelines integrating sources like MySQL, MongoDB, Kafka, and APIs into Redshift.

• Review automated QA outputs and resolve data quality issues.

• Detect and address anomalies such as missing data or delayed partitions.

• Execute standard fixes including DAG re-runs and metadata syncs.

• Escalate complex issues with clear documentation.

• Collaborate with QA and data engineers to improve test coverage and issue tracking.

• Maintain runbooks and report on data quality trends.

Desired experience:

• 1–3 years in data QA, operations, or analytics support.

• Proficient in SQL (ideally Redshift/PostgreSQL).

• Familiarity with ETL processes and data flow concepts.

• Strong attention to detail and problem-solving mindset.

• Clear written communication and a collaborative approach.

Nice to have: experience with Airflow, Flink, dbt, AWS services, Python scripting, and Iceberg/Parquet formats.